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The Rapid Adoption of Generative AI

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Abstract

Generative artificial intelligence (AI) is a potentially important new technology, but its impact on the economy depends on the speed and intensity of adoption. This paper reports results from a series of nationally representative U.S. surveys of generative AI use at work and at home. As of late 2024, 45% of the U.S. population age 18-64 uses generative AI. Among employed respondents, 27% used generative AI for work at least once in the previous week: 10% used it every workday, and 17% on some but not all workdays. Relative to each technology’s first mass-market product launch, work adoption of generative AI has been as fast as the personal computer (PC), and overall adoption has been faster than either PCs or the internet. Between 1 and 7% of all work hours are currently assisted by generative AI, and respondents report time savings equivalent to 1.4% of total work hours. Potential productivity gains vary widely by industry, and firm climate and policies play an important role in adoption patterns.

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  • Alexander Bick & Adam Blandin & David Deming, 2024. "The Rapid Adoption of Generative AI," Working Papers 2024-027, Federal Reserve Bank of St. Louis, revised 27 Oct 2025.
    • Handle: RePEc:fip:fedlwp:98805
    DOI: 10.20955/wp.2024.027
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    1. Alexander Bick & Adam Blandin & Karel Mertens, 2023. "Work from Home before and after the COVID-19 Outbreak," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(4), pages 1-39, October.
    2. David Autor, 2024. "Applying AI to Rebuild Middle Class Jobs," NBER Working Papers 32140, National Bureau of Economic Research, Inc.
    3. Alexander Bick & Adam Blandin, 2023. "Employer Reallocation During the COVID-19 Pandemic: Validation and Application of a Do-It-Yourself CPS," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 58-76, July.
    4. Kathryn Bonney & Cory Breaux & Catherine Buffington & Emin Dinlersoz & Lucia Foster & Nathan Goldschlag & John Haltiwanger & Zachary Kroff & Keith Savage, 2024. "Tracking Firm Use of AI in Real Time: A Snapshot from the Business Trends and Outlook Survey," Working Papers 24-16, Center for Economic Studies, U.S. Census Bureau.
    5. Diego Comin & Martí Mestieri, 2018. "If Technology Has Arrived Everywhere, Why Has Income Diverged?," American Economic Journal: Macroeconomics, American Economic Association, vol. 10(3), pages 137-178, July.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    7. Paul Beaudry & Mark Doms & Ethan Lewis, 2010. "Should the Personal Computer Be Considered a Technological Revolution? Evidence from U.S. Metropolitan Areas," Journal of Political Economy, University of Chicago Press, vol. 118(5), pages 988-1036.
    8. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
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    Cited by:

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    2. Masayuki MORIKAWA, 2024. "Macroeconomic Impact of Artificial Intelligence on Productivity: An estimate from a survey," Discussion papers 24084, Research Institute of Economy, Trade and Industry (RIETI).
    3. Zara Contractor & Germ'an Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," Papers 2508.00717, arXiv.org.
    4. Peeyush Agarwal & Harsh Agarwal & Akshat Rana, 2025. "What Work is AI Actually Doing? Uncovering the Drivers of Generative AI Adoption," Papers 2510.23669, arXiv.org, revised Oct 2025.
    5. Fabian Kosse & Tim Leffler & Arna Woemmel, 2025. "Digital Skills: Social Disparities and the Impact of Early Mentoring," SOEPpapers on Multidisciplinary Panel Data Research 1222, DIW Berlin, The German Socio-Economic Panel (SOEP).
    6. James Bono, 2025. "Randomized Controlled Trials for Phishing Triage Agent," Papers 2511.13860, arXiv.org.
    7. Contractor, Zara & Reyes, Germán, 2025. "Generative AI in Higher Education: Evidence from an Elite College," IZA Discussion Papers 18055, Institute of Labor Economics (IZA).
    8. Jacob Dominski & Yong Suk Lee, 2025. "Advancing AI Capabilities and Evolving Labor Outcomes," Papers 2507.08244, arXiv.org.
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    10. Piyush Gulati & Arianna Marchetti & Phanish Puranam & Victoria Sevcenko, 2025. "Generative AI Adoption and Higher Order Skills," Papers 2503.09212, arXiv.org, revised Jun 2025.
    11. Kiran Tomlinson & Sonia Jaffe & Will Wang & Scott Counts & Siddharth Suri, 2025. "Working with AI: Measuring the Applicability of Generative AI to Occupations," Papers 2507.07935, arXiv.org, revised Dec 2025.
    12. Aaron Chatterji & Daniel Rock & Eduard Talamàs, 2025. "Transformative AI and Firms," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    13. James Bono & Alec Xu, 2024. "Randomized Controlled Trials for Security Copilot for IT Administrators," Papers 2411.01067, arXiv.org, revised Nov 2024.
    14. Liu, Yan & Wang, He & Yu, Shu, 2025. "Labor Demand in the Age of Generative AI : Early Evidence from the U.S. Job Posting Data," Policy Research Working Paper Series 11263, The World Bank.
    15. Henry A. Thompson, 2024. "AI and the law," Papers 2412.05090, arXiv.org.
    16. James Bono & Beibei Cheng & Joaquin Lozano, 2025. "Randomized Controlled Trials for Conditional Access Optimization Agent," Papers 2511.13865, arXiv.org.
    17. Sugat Chaturvedi & Rochana Chaturvedi, 2025. "Who Gets the Callback? Generative AI and Gender Bias," Papers 2504.21400, arXiv.org.
    18. Liu, Yan & Huang, Jingyun & Wang, He, 2025. "Who on Earth Is Using Generative AI ? Global Trends and Shifts in 2025," Policy Research Working Paper Series 11231, The World Bank.
    19. Zara Contractor & Germán Reyes, 2025. "Generative AI in Higher Education: Evidence from an Elite College," CEDLAS, Working Papers 0359, CEDLAS, Universidad Nacional de La Plata.
    20. Fabian Kosse & Tim Leffler & Arna Woemmel, 2024. "Digital Skills: Social Disparities and the Impact of Early Mentoring," CESifo Working Paper Series 11570, CESifo.
    21. Lukas B. Freund & Lukas F. Mann, 2025. "Job Transformation, Specialization, and the Labor Market Effects of AI," CESifo Working Paper Series 12072, CESifo.
    22. Anastasios Evgenidis & Apostolos Fasianos, 2025. "AI news shocks and the macroeconomy: evidence from UK patent data," IFS Working Papers W25/48, Institute for Fiscal Studies.
    23. Leonardo Gambacorta & Tullio Jappelli & Tommaso Oliviero, 2025. "Exploring household adoption and usage of generative AI: new evidence from Italy," BIS Working Papers 1298, Bank for International Settlements.
    24. Eleanor W. Dillon & Sonia Jaffe & Nicole Immorlica & Christopher T. Stanton, 2025. "Shifting Work Patterns with Generative AI," NBER Working Papers 33795, National Bureau of Economic Research, Inc.
    25. Bertomeu, Jeremy & Lin, Yupeng & Liu, Yibin & Ni, Zhenghui, 2025. "The impact of generative AI on information processing: Evidence from the ban of ChatGPT in Italy," Journal of Accounting and Economics, Elsevier, vol. 80(1).

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    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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